Rapsodo Pte. Ltd.

Lodiya Radhakrishnan Vijayanand

Batuhan Okur

Roshan Gopalakrishnan

Saurabh Garg

Jin Xu

Kelvin Yeo Soon Keat

Nyan Myo Naing

Kelvin Soon Keat Yeo

An example method to determine an object spin rate may include training a neural network with a set of initial data. The set of initial data may be generated based on a plurality of initial radar signals of a plurality of initial objects in motion. The method may include receiving a radar signal of a particular object in motion. The method may include converting the radar signal into an input vector. The input vector may include time and frequency information of the particular object in motion. The method may include providing the input vector as input to a trained neural network. The method may include determining a spin rate of the particular object in motion based on an analysis performed by the trained neural. The analysis may include analyzing the input vector including time and frequency information of the object in motion in view of the set of initial data.

Detection and estimation of spin

A stump device may include a first image-capturing sensor configured to couple to at least one stump of a wicket positioned at a bowling end of a cricket field and capture image data of an initial motion of a cricket ball. The stump device may also include a second image-capturing sensor configured to couple to at least one stump of the wicket and capture image data of a trajectory and a flight path of the cricket ball. The stump device may additionally include a first radar sensor configured to couple to at least one stump of the wicket and capture radar data describing one or more initial launch parameters of the cricket ball. The stump device may include a second radar sensor configured to couple to at least one of the stumps of the wicket and capture radar data describing one or more movement parameters of a bowler.

Stump device for feature estimation of cricket games

A cricket sensor may include one or more first image-capturing sensors configured to capture image data of a pitching motion of a bowler and image data of an initial motion of a cricket ball at a bowling end of a cricket field. The cricket sensor may include one or more second image-capturing sensors configured to capture image data of a trajectory and a flight path of the cricket ball towards a batting end of the cricket field. The cricket sensor may also include one or more first radar sensors configured to capture radar data describing one or more initial launch parameters of the cricket ball related to the trajectory and the flight path of the cricket ball towards the batting end of the cricket field.

Feature estimation of a cricket game

An example method to determine an object spin rate may include receiving a radar signal of a particular object in motion. The method may further include converting the radar signal into an input vector. The method may also include providing the input vector as input to a neural network. The neural network may include access to a set of initial data that has been generated based on multiple initial radar signals of multiple initial objects in motion. The method may further include determining a spin rate of the particular object in motion based on an analysis performed by the neural network of the input vector including time and frequency information of the particular object in motion in view of the set of initial data. The analysis may include comparing one or more elements of the input vector to one or more elements of the set of initial data.

A method, including scanning a golf club to obtain scanning information; inputting the scanning information into a processing system; using at least one camera positioned behind and in-line to a golf swing direction and at least one lighting unit to obtain a series of images of a golf club during the golf swing; converting the series of images into parameterized motion representations; using at least one radar to obtain a radar signal; inputting the parameterized motion representations and the radar signal into the processing system; receiving golf club parameters and golf swing parameters as an output of the processing system; and generating a visual model of the golf club and the golf swing in a virtual space using the golf club parameters and the golf swing parameters.

Measurement and reconstruction of the golf launching scene in 3D

A golf launching monitoring arrangement allows equipment to be placed at a position behind the player (i.e., behind the golf ball), to measure both club and ball movement. A 3D scan of the club head before the play serves two purposes: 1) 3D registration that enables accurate measurement of the club head position and orientation for the camera system measuring the club movement from the back; 2) for reconstruction of the launching scene. With a 3D model of the club head, a simple 3D model of the golf ball and accurate measurement of their movement during the play, a full 3D golf launching scene can be reconstructed authentically. With this reconstruction, the movement of both the club head and the resulting ball movement can be replayed at any viewing angle, with any frame rate and at whatever resolution for the players or the coaches to view and analyze.

According to some embodiments, the present disclosure may relate to a method including transmitting a microwave towards a moving object and receiving a reflection of the microwave reflecting off of the moving object. The method may also include determining a speed of the moving object based on the reflection of the microwave and based on the speed of the moving object and a flight path distance of the moving object, determining an optimal photograph timeframe when the moving object is in a field of view of a camera. The method may further include automatically capturing a plurality of images during the optimal photograph timeframe.

Systems and methods of analyzing moving objects

The technologies described herein relate to measuring launch parameters of a flying object, such as a golf ball or a baseball. The laser based technology enables a system that is low cost which can measure launch parameters of a ball. The launch parameters are measured and rapid feedback is provided on each ball motion event and the data of every single ball launch data is stored in the backend server. The system may include a transmitter optical subassembly (TOSA), a receiver optical subassembly (ROSA), a primary processing unit, a camera subsystem, a data processing, a feedback display unit, and a backend server.

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Singapore, Singapore

Lodiya Radhakrishnan Vijayanand